An EEG-based method to decode cognitive factors in creative processes
File(s)
Author(s)
Yin, Yuan
Zuo, Haoyu
Childs, Peter RN
Type
Journal Article
Abstract
Neurotechnology has been applied to gain insights on creativity-related cognitive factors. Prior research has identified relations between cognitive factors and creativity qualitatively; while quantitative relations, such as the relative importance of cognitive factors and creativity, have not been fully determined. Therefore, taking the creative design process as an example, this study using electroencephalography (EEG) aims to objectively identify how creativity-related cognitive factors of retrieval, recall, association, and combination contribute to creativity. The theoretical basis for an EEG-based decoding method to objectively identify which cognitive factors occur in a creative process is developed. Thirty participants were recruited for a practical study to verify the reliability of the decoding method. Based on the methodology, relationships between the relative importance level of the cognitive factor and creative output quality levels were detected. Results indicated that the occurrence of recall and association are reported with a high reliability level by the decoding method. The results also indicated that association is the dominant cognitive factor for higher creative output quality levels. Recall is the dominant cognitive factor for lower creative output quality levels.
Date Issued
2023
Date Acceptance
2023-02-09
Citation
Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2023, 37
ISSN
0890-0604
Publisher
Cambridge University Press
Journal / Book Title
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Volume
37
Copyright Statement
© The Author(s), 2023. Published by
Cambridge University Press. This is an Open
Access article, distributed under the terms of
the Creative Commons Attribution licence
(http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted re-use, distribution
and reproduction, provided the original article
is properly cited.
Cambridge University Press. This is an Open
Access article, distributed under the terms of
the Creative Commons Attribution licence
(http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted re-use, distribution
and reproduction, provided the original article
is properly cited.
License URL
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000952391100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
ATTENTION
Cognitive factor
Computer Science
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
creativity process
decoding
DESIGN
DYNAMICS
EEG
Engineering
Engineering, Manufacturing
Engineering, Multidisciplinary
EPISODIC-SPECIFICITY INDUCTION
IDEATION
MEMORY
NETWORK
NEUROSCIENCE
regression analysis
Science & Technology
Technology
THINKING
THOUGHT
Publication Status
Published
Article Number
e12
Date Publish Online
2023-03-27